1. Field
The following description relates to a data processing method for clinical decision support system.
2. Description of the Related Art
For security and sharing of personal medical information, a recording system for storing and managing patients' medical records using electronic health recodes has been developed and utilized. The electronic health records contribute to provision of advanced medical services by sharing or exchanging medical information with various fields needing the medial information, as well as between medical institutes. Recently, with distribution of medical equipment capable of accurately measuring patients' health statuses and development of technologies including IT, NT and BT, private healthcare services such as Ubiquitous Healthcare have been introduced so that patients themselves can easily check their health statuses without having to visit hospitals.
In order to keep pace with the trend, studies into providing such healthcare services through a clinical decision support system are underway. The clinical decision support system is a computer-based support system designed to make a correct decision when a medical decision is needed, based on data measured or input from a patient and knowledge information of rule database. With realization of information of health and medical services, such as electronic health records and ubiquitous healthcare, concern with advanced medical services and reduction in time and cost is more increasing, and accordingly interest on the clinical decision support system is also increasing.
Electronic health records guidelines are generally stored in text files and are periodically updated by a user or system expert. In document “Clinical Decision Support System Architecture in Korea” by J. A. Kim, etc., International Conference on Convergence and Hybrid Information Technology, the authors have proposed inference mechanism with Electronic Health Record (HER) for existing hospital information systems. The inference mechanism can be applied to various healthcare fields including a clinical decision support system that is being actively studied.
Input data that is input to the clinical decision support system contains measurement is values about patients and knowledge about diseases. The input data is determined based on a rule, which generally is in the format of a natural language. The natural language is distinguished from constructed languages, such as machine languages, created for effective communications in specific technical fields. Since the natural language is different from machine languages used in computers or the like and computers can never understand the natural language, inputting data to a computer needs programming such as compiling for converting the natural language to a machine language. However, such programming needs help and intervention from experts, which is time consuming, resulting in low efficiency.
Furthermore, existing clinical decision support systems require very strict formats in applying an inference engine or in storing rules, so that a single rule storage does not allow the use of two or more inference engines having rules in different representational formats provided as input.
Therefore, in the case of a system dealing with expert content, like the clinical decision support system, data stored in rule database should be periodically updated with the help of medical doctors or programmers who are experts and participated in system manufacturing. However, the periodical update of data causes labor overheads as well as significant time consumption, resulting in inefficiency. These problems have become a major obstacle to application of the clinical decision support system to various fields.
Accordingly, in order to overcome the problems, a new clinical decision support system capable of efficiently updating rule database and allowing access of inference engines is needed.